Computed Tomography (CT) is a non-invasive imaging technique. One of the challenges in CT is that small features may be distorted or obscured due to the fact that these features may move during data acquisition. Since most image reconstruction techniques do not account for this motion, the resulting image includes image artifacts. These image artifacts may often severely distort small features, making segmentation tasks (e.g., vessel detection and vessel tracking, identification of lung nodules, etc.) challenging.
Therefore, it would be desirable to provide a system and method that accounts and compensates for the motion-induced artifacts that occur during image acquisition.